Video identification-based detection apparatus and method of vehicles against regulations

Abstract

The invention discloses a video identification-based detection apparatus and a method thereof of vehicles against regulations. The detection system comprises an upper supervisor, a control and transmission device, an infrared ray panoramic camera and a high speed close-up camera. The control and transmission device includes a video acquisition and conversion module, a rule arrangement module, a vehicle detection module, a peccancy analysis module, a camera control module, and a data wireless transmission module. According to the detection method, an image identification technology and a videotracking technology are applied, so that a problem of multi-target detection on vehicles against regulations is effectively solved and misjudgment on normal lane changing behaviors can be avoided; moreover, vehicles against regulations can be detected on the night condition and the condition of bad weather, wherein the vehicles are at the far distance. According to the invention, utilized equipment is perfect and the employed technology is mature; detection efficiency is high; detection cost is substantially reduced; and an efficiency and an intelligent level of traffic management are improved.

Description

technical field [0001] The invention belongs to the technical field of automatic detection of traffic violations, in particular to a device and method for detecting illegal vehicles based on video recognition. Background technique [0002] With the rapid increase of urban car ownership in our country, traffic violations are also occurring more and more frequently. Especially for road intersections, due to the large number of entrance lanes and the uneven queuing length of vehicles in each lane, behaviors such as malicious jamming and illegal compaction line changing are very common, which not only affects the normal driving of long-queuing traffic, but also easily Blocking the lane where the short-queue traffic flow is located affects the fairness of drivers who abide by the rules, and it is very easy to cause vehicle collision accidents and driver disputes. From April 1, 2010, in the newly revised and implemented "Regulations on Application and Use of Motor Vehicle Driving...

AI Technical Summary

Problems solved by technology

This system has the following defects: one is that it is necessary to excavate the road to bury the coil, if there is a failure or the service life of the coil itself ends, the road surface needs to be excavated for renovation or replacement; Long, tens of meters away from the stop line, so for illegal lane change control, the cost of embedding coils is very high; third, in the area where the lane line far from the stop line is a dotted line, it is impossible to distinguish between malicious traffic jams and normal traffic jams. Lane changing behavior, if the induction coil is still used for detection, it is easy to cause false shots and lead to disputes

However, this type of technology has several shortcomings: first, it generally lacks video tracking technology and pattern recognition technology, and can only capture red light running behaviors based on traffic light signals, and it is difficult to capture solid line lane changes and malicious blocking behaviors, and its applicability is low; The accuracy of the shooting range is high. If the shooting range crosses the stop line, the probability of taking a wrong shot will be high, and other vehicles in the camera's shooting screen will easily interfere with the post-processing; the third is that the camera's line of sight is easily blocked, making it difficult to capture large vehicles. Rear violating small car

[0006] Patent CN101593422B proposes a traffic violation detection method based on video tracking and pattern recognition. The pattern recognition technology and algorithm used in this method are not yet mature, and the research and development risks are high, so it is difficult to guarantee the accuracy and accuracy of detection

This detection method is even more incapable of dealing with the situation where multiple targets violate the rules at the same time

At the same time, this detection method is difficult to cope with the fleets that are closely following vehicles during peak hours, and cannot take pictures of illegal vehicles whose license plates are blocked by the vehicle in front

The detection method also does not work properly in bad weather

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